Are Tableau Data Types easy to Understand ?

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Todays digital world is data driven. Businesses, governments, finances, medical and many more organizations depend on data to operate their businesses and make future decision.

What is Data?

Data is collection of values that provides meaningful information. Data is raw facts and statistics collected to make future decision by analyzing and visualizing data, different trends, patterns and projection. Data can be categorize in many different types.

Below image shows Ambulatory data i.e. Patient Visit Id, Patient MRN, Provider ID , etc

What is Tableau?

Tableau is visual analytics tool that use to combine data analysis and interactive visualization. Tableau help users to turn raw data into visual insight, identify and understand trends, recognize patterns and make informed decisions through interactive reports. Understanding and managing data types is very important in Tableau for building accurate and meaningful visualization.

Tableau Data Types

There are 7 main data types in Tableau

1. Numeric Data Type

This data type contains numbers like integers or decimal values.

Example in below image Patient MRN column and Provider ID column has Number Values.

Above symbol represent Number value

Usage

• Numbers are commonly used as Measures in Tableau, where they can be aggregated (summed, averaged, etc.). For example, patient total, or provider total are numeric measures.

• Numeric fields are often placed on the Axes of visualizations like bar charts, line graphs, or scatter plots.

• You can perform arithmetic operations like addition, subtraction, or complex statistical calculations using numeric fields as Calculative Field

2. String Data Type

This data type contains text value. e.g. Name, Labels etc. String can also include digit or symbols.

Example in below image Visit Type column has string values

Above symbol represent String values

Usage

• Strings are typically used as Dimensions, meaning they categorize the data. For example, provider names or visit types can be dimensions in your visualizations.

• You can Filter visualizations based on string fields, such as filtering by specific types or names.

3. Date Data Type

This data type contains date value for any formate 'DD-MM-YYYY' or 'MM-DD-YYYY'. The date value represents specific time period, which is used for analysis over time, means monitoring changes in days, months or years.

Example in below image, Date of Visit column has date values

Above symbol represent Date values

Date and Time Data Type

An extension of date data type is date and time Data type. A date and time value can be continuous or discrete. It supports all formate of time. There is no time data type in tableau, so comparison will still look at the date component.

Example in below  image, Date Scheduled column has date and time values

Above symbol represent Date and Time Values

Usage

• Time Series Analysis: Dates are commonly used for time-based analyses, such as tracking sales over time, plotting trends, or analyzing seasonal patterns.

• Tableau can automatically generate Date Hierarchies (Year, Quarter, Month, Day) to allow you to drill down or roll up across time periods in your analysis.

• You can create date Filters for specific ranges (e.g., last month, last 30 days, etc.).

• Calculated Functions like DATEDIFF(), DATEADD(), and DATEPART() allow you to manipulate date fields, calculate differences between dates, or extract specific parts (e.g., year, month).

4. Geographical Data Type

This data type contains geographical field values such as 'Country name', 'Region','City name','Zip code' and 'territories'. Useful to see Geographical map view in tableau.

Example in below  image, City column and State column has geographical data values

Above symbol represent Geographical data values

Usage

• Geographic fields allow you to plot data on Maps. For example, if you have country or city names, Tableau can visualize this on a world map or regional map.

• Tableau has built-in Geocoding to automatically recognize geographic names, but you can also manually assign custom latitude and longitude data if needed.

  
  

5. Boolean Data Type

This data type contains numeric values like 'True' or 'False'. Boolean data type is binary data type which has only two type of values '0' or '1'. This data type is useful for categorized data in two distinct outcome.

Above symbol represent Boolean data values

Usage

• Boolean fields are useful for creating Filters that depend on conditions, such as showing only rows where a condition is TRUE.

• You can use Boolean fields to control the display of visualizations based on certain conditions (e.g., highlighting rows where profits are negative) is Conditional Formating

6. Cluster Data Type

This data type contains mixed value

Above symbol represent Cluster data values

7. Null Values

Null values represent missing or undefined data. Tableau highlights these null values so you can either account for or filter them out of your analysis.

Usage

• Tableau allows you to manage null values in visualizations. You can choose to filter them out, display them separately, or replace them with a default value.

• Use Null functions like ISNULL() to handle null values in calculations.

Conclusion

For anyone starting with Tableau, understanding its data types is an essential first step. Choosing the right data type ensures that your analysis is accurate, prevents errors, and helps adjusting Data Types in Tableau.

For most users, Tableau’s data types are straightforward and easy to understand. In short, if you’re wondering whether Tableau data types are easy to understand, the answer is a yes, especially if you’re starting with the basics.